We present an automated Image Annotation system called I-Tag which uses both visual and textual information of the images and recommends relevant tags for them. The automatic gene...
In image retrieval, most existing approaches that incorporate local features produce high dimensional vectors, which lead to a high computational and data storage cost. Moreover, ...
In this work, we are interested in technologies that will allow users to actively browse and navigate large image databases and to retrieve images through interactive fast browsin...
Image searching is a creative process. We have proposed a novel image retrieval system that supports creative search sessions by allowing the user to organise their search results ...
Abstract-- We aim for content-based image retrieval of textured objects in natural scenes under varying illumination and viewing conditions. To achieve this, image retrieval is bas...
In this paper, we propose a new type of image feature, which consists of patterns of colors and intensities that capture the latent associations among images and primitive feature...
A statistical correlation model for image retrieval is proposed. This model captures the semantic relationships among images in a database from simple statistics of userprovided r...
We introduce an image retrieval method for searchingan image database by using a query image that has similarity in its global and/or regional image contents to the intended targe...
We investigate the properties of a metric between two distributions, the Earth Mover's Distance (EMD), for content-based image retrieval. The EMD is based on the minimal cost ...